{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from utility import *\n",
    "\n",
    "from collections import Counter\n",
    "from scipy.stats import ks_2samp\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import random\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dataset Loading"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data sets needed for the loaders can be found at snap.stanford.edu/decagon. The side effect information was curated from the TWOSIDES, OFFSIDES, and Sider databases."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading: bio-decagon-combo.csv\n",
      "Drug combinations: 63473 Side effects: 1318\n",
      "Drug-drug interactions: 4651131\n",
      "Reading: bio-decagon-ppi.csv\n",
      "Edges: 715612\n",
      "Nodes: 19081\n",
      "Reading: bio-decagon-mono.csv\n",
      "Reading: bio-decagon-targets-all.csv\n",
      "Reading: bio-decagon-effectcategories.csv\n"
     ]
    }
   ],
   "source": [
    "combo2stitch, combo2se, se2name = load_combo_se()\n",
    "net, node2idx = load_ppi()\n",
    "stitch2se, se2name_mono = load_mono_se()\n",
    "stitch2proteins = load_targets(fname='bio-decagon-targets-all.csv')\n",
    "se2class, se2name_class = load_categories()\n",
    "se2name.update(se2name_mono)\n",
    "se2name.update(se2name_class)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Basic Statistics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How many side effects does each drug combination have?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def plot_distribution(dist, title=\"\", x_label=\"\", y_label=\"\", file_name=None):\n",
    "    plt.figure(figsize=(6, 3.5))\n",
    "    sns.set_context(\"paper\", font_scale=1.8)\n",
    "    sns.set_style('ticks')\n",
    "    sns.set_style({\"xtick.direction\": \"in\", \"ytick.direction\": \"in\"})\n",
    "    sns.distplot(dist, kde=False, color=sns.xkcd_rgb['red'], bins=20, hist_kws={\"alpha\" : 1})\n",
    "    plt.xlabel(x_label)\n",
    "    plt.title(title)\n",
    "    plt.tight_layout()\n",
    "    plt.gcf().subplots_adjust(left=0.2, right=0.8, top=0.8, bottom=0.2)\n",
    "    plt.ylabel(y_label)\n",
    "    if file_name:\n",
    "        plt.savefig(file_name)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Median number of side effects per drug combination 53.0\n"
     ]
    },
    {
     "data": {
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WLxD/Uf8XWIvYpXst8AlwUjvZWmT3OsDRQLYeQDvauirwVJq34MALGrvtZu8Z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\nKHLgQgjRociBCyFEh/L/Afv55NlgelvJAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a2b05bf50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "distribution_combos = [len(combo2se[combo]) for combo in combo2se]\n",
    "print \"Median number of side effects per drug combination\", np.median(distribution_combos)\n",
    "plot_distribution(distribution_combos, \"\", \"Number of Side Effects\", \"Number of \\n Drug Combinations\", \"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How frequent are different side effects?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Most common side effects in drug combinations:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Frequency in Drug Combos</th>\n",
       "      <th>Name</th>\n",
       "      <th>Side Effect</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>28568</td>\n",
       "      <td>arterial pressure NOS decreased</td>\n",
       "      <td>C0020649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>27006</td>\n",
       "      <td>anaemia</td>\n",
       "      <td>C0002871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>26037</td>\n",
       "      <td>Difficulty breathing</td>\n",
       "      <td>C0013404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>25190</td>\n",
       "      <td>nausea</td>\n",
       "      <td>C0027497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24430</td>\n",
       "      <td>neumonia</td>\n",
       "      <td>C0032285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>24260</td>\n",
       "      <td>Fatigue</td>\n",
       "      <td>C0015672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>23894</td>\n",
       "      <td>Pain</td>\n",
       "      <td>C0030193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>23848</td>\n",
       "      <td>diarrhea</td>\n",
       "      <td>C0011991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>23515</td>\n",
       "      <td>asthenia</td>\n",
       "      <td>C0004093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>23043</td>\n",
       "      <td>emesis</td>\n",
       "      <td>C0042963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>21981</td>\n",
       "      <td>edema extremities</td>\n",
       "      <td>C0085649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>21806</td>\n",
       "      <td>body temperature increased</td>\n",
       "      <td>C0015967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>21781</td>\n",
       "      <td>pleural pain</td>\n",
       "      <td>C0008033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>21410</td>\n",
       "      <td>abdominal pain</td>\n",
       "      <td>C0000737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>21322</td>\n",
       "      <td>Hypoventilation</td>\n",
       "      <td>C0398353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>21013</td>\n",
       "      <td>chest pain</td>\n",
       "      <td>C0008031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>20204</td>\n",
       "      <td>dizziness</td>\n",
       "      <td>C0012833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>19930</td>\n",
       "      <td>Back Ache</td>\n",
       "      <td>C0004604</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19803</td>\n",
       "      <td>Head ache</td>\n",
       "      <td>C0018681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19376</td>\n",
       "      <td>High blood pressure</td>\n",
       "      <td>C0020538</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Frequency in Drug Combos                             Name Side Effect\n",
       "0                      28568  arterial pressure NOS decreased    C0020649\n",
       "1                      27006                          anaemia    C0002871\n",
       "2                      26037             Difficulty breathing    C0013404\n",
       "3                      25190                           nausea    C0027497\n",
       "4                      24430                         neumonia    C0032285\n",
       "5                      24260                          Fatigue    C0015672\n",
       "6                      23894                             Pain    C0030193\n",
       "7                      23848                         diarrhea    C0011991\n",
       "8                      23515                         asthenia    C0004093\n",
       "9                      23043                           emesis    C0042963\n",
       "10                     21981                edema extremities    C0085649\n",
       "11                     21806       body temperature increased    C0015967\n",
       "12                     21781                     pleural pain    C0008033\n",
       "13                     21410                   abdominal pain    C0000737\n",
       "14                     21322                  Hypoventilation    C0398353\n",
       "15                     21013                       chest pain    C0008031\n",
       "16                     20204                        dizziness    C0012833\n",
       "17                     19930                        Back Ache    C0004604\n",
       "18                     19803                        Head ache    C0018681\n",
       "19                     19376              High blood pressure    C0020538"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import display, HTML\n",
    "\n",
    "def get_se_counter(se_map):\n",
    "    side_effects = []\n",
    "    for drug in se_map:\n",
    "        side_effects += list(set(se_map[drug]))\n",
    "    return Counter(side_effects)\n",
    "\n",
    "combo_counter = get_se_counter(combo2se)\n",
    "\n",
    "print(\"Most common side effects in drug combinations:\")\n",
    "common_se = []\n",
    "common_se_counts = []\n",
    "common_se_names = []\n",
    "for se, count in combo_counter.most_common(20):\n",
    "    common_se += [se]\n",
    "    common_se_counts += [count]\n",
    "    common_se_names += [se2name[se]]\n",
    "df = pd.DataFrame(data={\"Side Effect\": common_se, \"Frequency in Drug Combos\": common_se_counts, \"Name\": common_se_names})  \n",
    "display(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot of Side Effect Frequency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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kZs2ahdZL0hRCPC/0Sppff/01o0aNwsfHx9TxAJCcnIyfnx+HDx+mUqVKdO3a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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a2b5b1d50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_distribution(np.log10(np.asarray(list(zip(*combo_counter.items())[1]))), \"\",  \"Log(Number of Drug Combinations)\", \"Number of Side Effects\", file_name=\"se_combodist.pdf\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Side Effect Cooccurrence in Drug Combinations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "combos = combo2se.keys()\n",
    "combo_probability_distribution = np.asarray([len(combo2se[combo])*1.0 for combo in combo2se])\n",
    "combo_probability_distribution = combo_probability_distribution/np.sum(combo_probability_distribution)\n",
    "\n",
    "se2combo = defaultdict(set)\n",
    "for combo in combo2se:\n",
    "    for se in combo2se[combo]:\n",
    "        se2combo[se].add(combo)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We observe that polypharmacy side effects do not appear independently of one another in co-prescribed drug pairs (\\ie, drug combinations), suggesting that joint modeling over multiple side effects can aid in the prediction task. To quantify the co-occurrence between side effects, we count the number of drug combinations in which a given side effect co-occurs with other side effects, and then use permutation testing with a null model of random co-occurrence. As exemplified for hypertension and nausea below, we find that the majority of the most common side effects are either significantly overrepresented or underrepresented with respect to how often they co-occur with nausea/hypertension as side effects in drug combinations, at $\\alpha=0.05$. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Permutation test testing the significancy between the drug combinations a side effect occurs in,\n",
    "# as compared to other common side effects\n",
    "def run_permutation_test(se_oi, num_permutations = 2000):\n",
    "    se_oi_combos = se2combo[se_oi]\n",
    "    side_effects = []\n",
    "    names = []\n",
    "    real_overlaps = []\n",
    "    mean_permuted_overlap = []\n",
    "    probabilities = []\n",
    "    for se, count in combo_counter.most_common(51):\n",
    "        if se == se_oi:\n",
    "            continue\n",
    "        real_combos = se2combo[se]\n",
    "        real_overlap = len(real_combos.intersection(se_oi_combos))\n",
    "        permuted_overlaps = []\n",
    "        for i in range(num_permutations):\n",
    "            combo_sample = np.random.choice(combos, len(real_combos), replace=False, p=combo_probability_distribution)\n",
    "            permuted_overlaps += [len(se_oi_combos.intersection(set(combo_sample)))]\n",
    "        probability = np.sum(np.asarray(permuted_overlaps) >= real_overlap)*1.0/num_permutations\n",
    "        side_effects += [se]\n",
    "        names += [se2name[se]]\n",
    "        real_overlaps += [real_overlap]\n",
    "        mean_permuted_overlap += [np.mean(permuted_overlaps)]\n",
    "        probabilities += [probability]\n",
    "    df = pd.DataFrame(data={\"Side Effect\": side_effects, \"True Overlap\": real_overlaps, \"Mean Permuted Overlap\": mean_permuted_overlap, \"Probability True < Permuted\": probabilities, \"Name\": names})  \n",
    "    df = df[['Side Effect', 'Name', 'True Overlap', 'Mean Permuted Overlap', 'Probability True < Permuted']]\n",
    "    display(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Side Effect</th>\n",
       "      <th>Name</th>\n",
       "      <th>True Overlap</th>\n",
       "      <th>Mean Permuted Overlap</th>\n",
       "      <th>Probability True &lt; Permuted</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>C0020649</td>\n",
       "      <td>arterial pressure NOS decreased</td>\n",
       "      <td>10557</td>\n",
       "      <td>11168.6310</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>C0002871</td>\n",
       "      <td>anaemia</td>\n",
       "      <td>9457</td>\n",
       "      <td>10625.5935</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>C0013404</td>\n",
       "      <td>Difficulty breathing</td>\n",
       "      <td>9974</td>\n",
       "      <td>10284.1575</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>C0027497</td>\n",
       "      <td>nausea</td>\n",
       "      <td>9326</td>\n",
       "      <td>9983.4730</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>C0032285</td>\n",
       "      <td>neumonia</td>\n",
       "      <td>9032</td>\n",
       "      <td>9710.2255</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>C0015672</td>\n",
       "      <td>Fatigue</td>\n",
       "      <td>9169</td>\n",
       "      <td>9648.1485</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>C0030193</td>\n",
       "      <td>Pain</td>\n",
       "      <td>9804</td>\n",
       "      <td>9517.4920</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>C0011991</td>\n",
       "      <td>diarrhea</td>\n",
       "      <td>8625</td>\n",
       "      <td>9499.6700</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>C0004093</td>\n",
       "      <td>asthenia</td>\n",
       "      <td>9150</td>\n",
       "      <td>9379.2765</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>C0042963</td>\n",
       "      <td>emesis</td>\n",
       "      <td>8227</td>\n",
       "      <td>9205.6620</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>C0085649</td>\n",
       "      <td>edema extremities</td>\n",
       "      <td>9011</td>\n",
       "      <td>8818.5175</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>C0015967</td>\n",
       "      <td>body temperature increased</td>\n",
       "      <td>7536</td>\n",
       "      <td>8752.6295</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>C0008033</td>\n",
       "      <td>pleural pain</td>\n",
       "      <td>8941</td>\n",
       "      <td>8741.9640</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>C0000737</td>\n",
       "      <td>abdominal pain</td>\n",
       "      <td>8923</td>\n",
       "      <td>8605.4555</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>C0398353</td>\n",
       "      <td>Hypoventilation</td>\n",
       "      <td>9926</td>\n",
       "      <td>8571.8495</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>C0008031</td>\n",
       "      <td>chest pain</td>\n",
       "      <td>9986</td>\n",
       "      <td>8458.9515</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>C0012833</td>\n",
       "      <td>dizziness</td>\n",
       "      <td>8409</td>\n",
       "      <td>8155.1085</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>C0004604</td>\n",
       "      <td>Back Ache</td>\n",
       "      <td>8879</td>\n",
       "      <td>8053.4790</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>C0018681</td>\n",
       "      <td>Head ache</td>\n",
       "      <td>8402</td>\n",
       "      <td>8006.1115</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>C0009676</td>\n",
       "      <td>confusion</td>\n",
       "      <td>7311</td>\n",
       "      <td>7840.3240</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>C0011175</td>\n",
       "      <td>dehydration</td>\n",
       "      <td>6877</td>\n",
       "      <td>7740.0310</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>C0003467</td>\n",
       "      <td>Anxiety</td>\n",
       "      <td>8695</td>\n",
       "      <td>7695.4900</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>C0035078</td>\n",
       "      <td>kidney failure</td>\n",
       "      <td>7261</td>\n",
       "      <td>7660.8715</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>C0043096</td>\n",
       "      <td>loss of weight</td>\n",
       "      <td>7523</td>\n",
       "      <td>7621.0155</td>\n",
       "      <td>0.9735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>C0020456</td>\n",
       "      <td>hyperglycaemia</td>\n",
       "      <td>7886</td>\n",
       "      <td>7617.4375</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>C0013604</td>\n",
       "      <td>edema</td>\n",
       "      <td>7163</td>\n",
       "      <td>7482.2830</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>C0003123</td>\n",
       "      <td>Anorexia</td>\n",
       "      <td>6811</td>\n",
       "      <td>7388.9615</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>C0003862</td>\n",
       "      <td>Aching joints</td>\n",
       "      <td>7994</td>\n",
       "      <td>7344.9990</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>C0022660</td>\n",
       "      <td>acute kidney failure</td>\n",
       "      <td>6381</td>\n",
       "      <td>7302.7290</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>C0442874</td>\n",
       "      <td>neuropathy</td>\n",
       "      <td>7938</td>\n",
       "      <td>7286.8275</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>C0030196</td>\n",
       "      <td>Extremity pain</td>\n",
       "      <td>7676</td>\n",
       "      <td>7247.0995</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>C0042029</td>\n",
       "      <td>Infection Urinary Tract</td>\n",
       "      <td>7502</td>\n",
       "      <td>7192.1085</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>C0010200</td>\n",
       "      <td>Cough</td>\n",
       "      <td>7260</td>\n",
       "      <td>7186.2450</td>\n",
       "      <td>0.0625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>C0009806</td>\n",
       "      <td>constipated</td>\n",
       "      <td>7481</td>\n",
       "      <td>7183.9235</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>C0039231</td>\n",
       "      <td>heart rate increased</td>\n",
       "      <td>7089</td>\n",
       "      <td>7156.0390</td>\n",
       "      <td>0.9260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>C0043094</td>\n",
       "      <td>weight gain</td>\n",
       "      <td>7621</td>\n",
       "      <td>6981.6530</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>C0040034</td>\n",
       "      <td>thrombocytopenia</td>\n",
       "      <td>5300</td>\n",
       "      <td>6961.4105</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>C0032227</td>\n",
       "      <td>Pleural Effusion</td>\n",
       "      <td>6137</td>\n",
       "      <td>6900.5185</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>C0243026</td>\n",
       "      <td>sepsis</td>\n",
       "      <td>5680</td>\n",
       "      <td>6773.1200</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>C0018802</td>\n",
       "      <td>Cardiac decompensation</td>\n",
       "      <td>7612</td>\n",
       "      <td>6766.7475</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>C0027051</td>\n",
       "      <td>heart attack</td>\n",
       "      <td>8271</td>\n",
       "      <td>6692.5900</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>C1145670</td>\n",
       "      <td>respiratory failure</td>\n",
       "      <td>5855</td>\n",
       "      <td>6536.9340</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>C0004238</td>\n",
       "      <td>AFIB</td>\n",
       "      <td>6278</td>\n",
       "      <td>6386.6380</td>\n",
       "      <td>0.9880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>C0013144</td>\n",
       "      <td>drowsiness</td>\n",
       "      <td>6195</td>\n",
       "      <td>6374.8605</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>C0015230</td>\n",
       "      <td>eruption</td>\n",
       "      <td>5653</td>\n",
       "      <td>6367.9340</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>C0917801</td>\n",
       "      <td>insomnia</td>\n",
       "      <td>6756</td>\n",
       "      <td>6339.0310</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>C0037763</td>\n",
       "      <td>muscle spasm</td>\n",
       "      <td>6867</td>\n",
       "      <td>6290.1030</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>C0038454</td>\n",
       "      <td>apoplexy</td>\n",
       "      <td>8084</td>\n",
       "      <td>6253.6085</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>C0027947</td>\n",
       "      <td>Neutropenia</td>\n",
       "      <td>4426</td>\n",
       "      <td>6228.8030</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>C0020625</td>\n",
       "      <td>blood sodium decreased</td>\n",
       "      <td>5353</td>\n",
       "      <td>6031.0370</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Side Effect                             Name  True Overlap  \\\n",
       "0     C0020649  arterial pressure NOS decreased         10557   \n",
       "1     C0002871                          anaemia          9457   \n",
       "2     C0013404             Difficulty breathing          9974   \n",
       "3     C0027497                           nausea          9326   \n",
       "4     C0032285                         neumonia          9032   \n",
       "5     C0015672                          Fatigue          9169   \n",
       "6     C0030193                             Pain          9804   \n",
       "7     C0011991                         diarrhea          8625   \n",
       "8     C0004093                         asthenia          9150   \n",
       "9     C0042963                           emesis          8227   \n",
       "10    C0085649                edema extremities          9011   \n",
       "11    C0015967       body temperature increased          7536   \n",
       "12    C0008033                     pleural pain          8941   \n",
       "13    C0000737                   abdominal pain          8923   \n",
       "14    C0398353                  Hypoventilation          9926   \n",
       "15    C0008031                       chest pain          9986   \n",
       "16    C0012833                        dizziness          8409   \n",
       "17    C0004604                        Back Ache          8879   \n",
       "18    C0018681                        Head ache          8402   \n",
       "19    C0009676                        confusion          7311   \n",
       "20    C0011175                      dehydration          6877   \n",
       "21    C0003467                          Anxiety          8695   \n",
       "22    C0035078                   kidney failure          7261   \n",
       "23    C0043096                   loss of weight          7523   \n",
       "24    C0020456                   hyperglycaemia          7886   \n",
       "25    C0013604                            edema          7163   \n",
       "26    C0003123                         Anorexia          6811   \n",
       "27    C0003862                    Aching joints          7994   \n",
       "28    C0022660             acute kidney failure          6381   \n",
       "29    C0442874                       neuropathy          7938   \n",
       "30    C0030196                   Extremity pain          7676   \n",
       "31    C0042029          Infection Urinary Tract          7502   \n",
       "32    C0010200                            Cough          7260   \n",
       "33    C0009806                      constipated          7481   \n",
       "34    C0039231             heart rate increased          7089   \n",
       "35    C0043094                      weight gain          7621   \n",
       "36    C0040034                 thrombocytopenia          5300   \n",
       "37    C0032227                 Pleural Effusion          6137   \n",
       "38    C0243026                           sepsis          5680   \n",
       "39    C0018802           Cardiac decompensation          7612   \n",
       "40    C0027051                     heart attack          8271   \n",
       "41    C1145670              respiratory failure          5855   \n",
       "42    C0004238                             AFIB          6278   \n",
       "43    C0013144                       drowsiness          6195   \n",
       "44    C0015230                         eruption          5653   \n",
       "45    C0917801                         insomnia          6756   \n",
       "46    C0037763                     muscle spasm          6867   \n",
       "47    C0038454                         apoplexy          8084   \n",
       "48    C0027947                      Neutropenia          4426   \n",
       "49    C0020625           blood sodium decreased          5353   \n",
       "\n",
       "    Mean Permuted Overlap  Probability True < Permuted  \n",
       "0              11168.6310                       1.0000  \n",
       "1              10625.5935                       1.0000  \n",
       "2              10284.1575                       1.0000  \n",
       "3               9983.4730                       1.0000  \n",
       "4               9710.2255                       1.0000  \n",
       "5               9648.1485                       1.0000  \n",
       "6               9517.4920                       0.0000  \n",
       "7               9499.6700                       1.0000  \n",
       "8               9379.2765                       1.0000  \n",
       "9               9205.6620                       1.0000  \n",
       "10              8818.5175                       0.0000  \n",
       "11              8752.6295                       1.0000  \n",
       "12              8741.9640                       0.0000  \n",
       "13              8605.4555                       0.0000  \n",
       "14              8571.8495                       0.0000  \n",
       "15              8458.9515                       0.0000  \n",
       "16              8155.1085                       0.0000  \n",
       "17              8053.4790                       0.0000  \n",
       "18              8006.1115                       0.0000  \n",
       "19              7840.3240                       1.0000  \n",
       "20              7740.0310                       1.0000  \n",
       "21              7695.4900                       0.0000  \n",
       "22              7660.8715                       1.0000  \n",
       "23              7621.0155                       0.9735  \n",
       "24              7617.4375                       0.0000  \n",
       "25              7482.2830                       1.0000  \n",
       "26              7388.9615                       1.0000  \n",
       "27              7344.9990                       0.0000  \n",
       "28              7302.7290                       1.0000  \n",
       "29              7286.8275                       0.0000  \n",
       "30              7247.0995                       0.0000  \n",
       "31              7192.1085                       0.0000  \n",
       "32              7186.2450                       0.0625  \n",
       "33              7183.9235                       0.0000  \n",
       "34              7156.0390                       0.9260  \n",
       "35              6981.6530                       0.0000  \n",
       "36              6961.4105                       1.0000  \n",
       "37              6900.5185                       1.0000  \n",
       "38              6773.1200                       1.0000  \n",
       "39              6766.7475                       0.0000  \n",
       "40              6692.5900                       0.0000  \n",
       "41              6536.9340                       1.0000  \n",
       "42              6386.6380                       0.9880  \n",
       "43              6374.8605                       1.0000  \n",
       "44              6367.9340                       1.0000  \n",
       "45              6339.0310                       0.0000  \n",
       "46              6290.1030                       0.0000  \n",
       "47              6253.6085                       0.0000  \n",
       "48              6228.8030                       1.0000  \n",
       "49              6031.0370                       1.0000  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# For hypertension\n",
    "run_permutation_test('C0020538')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Side Effect</th>\n",
       "      <th>Name</th>\n",
       "      <th>True Overlap</th>\n",
       "      <th>Mean Permuted Overlap</th>\n",
       "      <th>Probability True &lt; Permuted</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>C0020649</td>\n",
       "      <td>arterial pressure NOS decreased</td>\n",
       "      <td>13623</td>\n",
       "      <td>13817.6665</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>C0002871</td>\n",
       "      <td>anaemia</td>\n",
       "      <td>12668</td>\n",
       "      <td>13141.3570</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>C0013404</td>\n",
       "      <td>Difficulty breathing</td>\n",
       "      <td>12823</td>\n",
       "      <td>12715.3290</td>\n",
       "      <td>0.0215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>C0032285</td>\n",
       "      <td>neumonia</td>\n",
       "      <td>11075</td>\n",
       "      <td>11998.8955</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>C0015672</td>\n",
       "      <td>Fatigue</td>\n",
       "      <td>13570</td>\n",
       "      <td>11921.7745</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>C0030193</td>\n",
       "      <td>Pain</td>\n",
       "      <td>12699</td>\n",
       "      <td>11760.4490</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>C0011991</td>\n",
       "      <td>diarrhea</td>\n",
       "      <td>13492</td>\n",
       "      <td>11740.9805</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>C0004093</td>\n",
       "      <td>asthenia</td>\n",
       "      <td>13137</td>\n",
       "      <td>11587.6845</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>C0042963</td>\n",
       "      <td>emesis</td>\n",
       "      <td>16363</td>\n",
       "      <td>11377.2805</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>C0085649</td>\n",
       "      <td>edema extremities</td>\n",
       "      <td>11139</td>\n",
       "      <td>10890.9000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>C0015967</td>\n",
       "      <td>body temperature increased</td>\n",
       "      <td>10861</td>\n",
       "      <td>10811.9245</td>\n",
       "      <td>0.1760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>C0008033</td>\n",
       "      <td>pleural pain</td>\n",
       "      <td>11890</td>\n",
       "      <td>10799.2440</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>C0000737</td>\n",
       "      <td>abdominal pain</td>\n",
       "      <td>12145</td>\n",
       "      <td>10627.1125</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>C0398353</td>\n",
       "      <td>Hypoventilation</td>\n",
       "      <td>11109</td>\n",
       "      <td>10590.1065</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>C0008031</td>\n",
       "      <td>chest pain</td>\n",
       "      <td>11003</td>\n",
       "      <td>10448.3195</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>C0012833</td>\n",
       "      <td>dizziness</td>\n",
       "      <td>11644</td>\n",
       "      <td>10073.0220</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>C0004604</td>\n",
       "      <td>Back Ache</td>\n",
       "      <td>11152</td>\n",
       "      <td>9944.3010</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>C0018681</td>\n",
       "      <td>Head ache</td>\n",
       "      <td>11346</td>\n",
       "      <td>9883.8600</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>C0020538</td>\n",
       "      <td>High blood pressure</td>\n",
       "      <td>9326</td>\n",
       "      <td>9689.2270</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>C0009676</td>\n",
       "      <td>confusion</td>\n",
       "      <td>9862</td>\n",
       "      <td>9681.1065</td>\n",
       "      <td>0.0005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>C0011175</td>\n",
       "      <td>dehydration</td>\n",
       "      <td>10291</td>\n",
       "      <td>9557.3490</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>C0003467</td>\n",
       "      <td>Anxiety</td>\n",
       "      <td>10263</td>\n",
       "      <td>9503.0730</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>C0035078</td>\n",
       "      <td>kidney failure</td>\n",
       "      <td>8367</td>\n",
       "      <td>9461.2210</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>C0043096</td>\n",
       "      <td>loss of weight</td>\n",
       "      <td>10683</td>\n",
       "      <td>9411.3420</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>C0020456</td>\n",
       "      <td>hyperglycaemia</td>\n",
       "      <td>9321</td>\n",
       "      <td>9408.8050</td>\n",
       "      <td>0.9595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>C0013604</td>\n",
       "      <td>edema</td>\n",
       "      <td>8827</td>\n",
       "      <td>9240.2495</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>C0003123</td>\n",
       "      <td>Anorexia</td>\n",
       "      <td>11131</td>\n",
       "      <td>9124.1175</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>C0003862</td>\n",
       "      <td>Aching joints</td>\n",
       "      <td>9981</td>\n",
       "      <td>9071.0055</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>C0022660</td>\n",
       "      <td>acute kidney failure</td>\n",
       "      <td>8075</td>\n",
       "      <td>9016.2585</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>C0442874</td>\n",
       "      <td>neuropathy</td>\n",
       "      <td>9087</td>\n",
       "      <td>9001.2190</td>\n",
       "      <td>0.0470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>C0030196</td>\n",
       "      <td>Extremity pain</td>\n",
       "      <td>9742</td>\n",
       "      <td>8948.4745</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>C0042029</td>\n",
       "      <td>Infection Urinary Tract</td>\n",
       "      <td>9281</td>\n",
       "      <td>8879.6780</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>C0010200</td>\n",
       "      <td>Cough</td>\n",
       "      <td>9406</td>\n",
       "      <td>8874.1120</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>C0009806</td>\n",
       "      <td>constipated</td>\n",
       "      <td>10229</td>\n",
       "      <td>8871.6220</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>C0039231</td>\n",
       "      <td>heart rate increased</td>\n",
       "      <td>8770</td>\n",
       "      <td>8837.0945</td>\n",
       "      <td>0.9020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>C0043094</td>\n",
       "      <td>weight gain</td>\n",
       "      <td>8956</td>\n",
       "      <td>8620.5610</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>C0040034</td>\n",
       "      <td>thrombocytopenia</td>\n",
       "      <td>7512</td>\n",
       "      <td>8596.8345</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>C0032227</td>\n",
       "      <td>Pleural Effusion</td>\n",
       "      <td>7840</td>\n",
       "      <td>8516.5250</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>C0243026</td>\n",
       "      <td>sepsis</td>\n",
       "      <td>7473</td>\n",
       "      <td>8367.0850</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>C0018802</td>\n",
       "      <td>Cardiac decompensation</td>\n",
       "      <td>7753</td>\n",
       "      <td>8354.2405</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>C0027051</td>\n",
       "      <td>heart attack</td>\n",
       "      <td>7721</td>\n",
       "      <td>8267.0380</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>C1145670</td>\n",
       "      <td>respiratory failure</td>\n",
       "      <td>7169</td>\n",
       "      <td>8072.5870</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>C0004238</td>\n",
       "      <td>AFIB</td>\n",
       "      <td>6995</td>\n",
       "      <td>7886.3295</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>C0013144</td>\n",
       "      <td>drowsiness</td>\n",
       "      <td>7976</td>\n",
       "      <td>7871.2930</td>\n",
       "      <td>0.0160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>C0015230</td>\n",
       "      <td>eruption</td>\n",
       "      <td>7785</td>\n",
       "      <td>7860.9235</td>\n",
       "      <td>0.9425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>C0917801</td>\n",
       "      <td>insomnia</td>\n",
       "      <td>8845</td>\n",
       "      <td>7825.6305</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>C0037763</td>\n",
       "      <td>muscle spasm</td>\n",
       "      <td>8537</td>\n",
       "      <td>7769.9140</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>C0038454</td>\n",
       "      <td>apoplexy</td>\n",
       "      <td>7332</td>\n",
       "      <td>7722.1020</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>C0027947</td>\n",
       "      <td>Neutropenia</td>\n",
       "      <td>6996</td>\n",
       "      <td>7691.7345</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>C0020625</td>\n",
       "      <td>blood sodium decreased</td>\n",
       "      <td>7267</td>\n",
       "      <td>7447.0185</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Side Effect                             Name  True Overlap  \\\n",
       "0     C0020649  arterial pressure NOS decreased         13623   \n",
       "1     C0002871                          anaemia         12668   \n",
       "2     C0013404             Difficulty breathing         12823   \n",
       "3     C0032285                         neumonia         11075   \n",
       "4     C0015672                          Fatigue         13570   \n",
       "5     C0030193                             Pain         12699   \n",
       "6     C0011991                         diarrhea         13492   \n",
       "7     C0004093                         asthenia         13137   \n",
       "8     C0042963                           emesis         16363   \n",
       "9     C0085649                edema extremities         11139   \n",
       "10    C0015967       body temperature increased         10861   \n",
       "11    C0008033                     pleural pain         11890   \n",
       "12    C0000737                   abdominal pain         12145   \n",
       "13    C0398353                  Hypoventilation         11109   \n",
       "14    C0008031                       chest pain         11003   \n",
       "15    C0012833                        dizziness         11644   \n",
       "16    C0004604                        Back Ache         11152   \n",
       "17    C0018681                        Head ache         11346   \n",
       "18    C0020538              High blood pressure          9326   \n",
       "19    C0009676                        confusion          9862   \n",
       "20    C0011175                      dehydration         10291   \n",
       "21    C0003467                          Anxiety         10263   \n",
       "22    C0035078                   kidney failure          8367   \n",
       "23    C0043096                   loss of weight         10683   \n",
       "24    C0020456                   hyperglycaemia          9321   \n",
       "25    C0013604                            edema          8827   \n",
       "26    C0003123                         Anorexia         11131   \n",
       "27    C0003862                    Aching joints          9981   \n",
       "28    C0022660             acute kidney failure          8075   \n",
       "29    C0442874                       neuropathy          9087   \n",
       "30    C0030196                   Extremity pain          9742   \n",
       "31    C0042029          Infection Urinary Tract          9281   \n",
       "32    C0010200                            Cough          9406   \n",
       "33    C0009806                      constipated         10229   \n",
       "34    C0039231             heart rate increased          8770   \n",
       "35    C0043094                      weight gain          8956   \n",
       "36    C0040034                 thrombocytopenia          7512   \n",
       "37    C0032227                 Pleural Effusion          7840   \n",
       "38    C0243026                           sepsis          7473   \n",
       "39    C0018802           Cardiac decompensation          7753   \n",
       "40    C0027051                     heart attack          7721   \n",
       "41    C1145670              respiratory failure          7169   \n",
       "42    C0004238                             AFIB          6995   \n",
       "43    C0013144                       drowsiness          7976   \n",
       "44    C0015230                         eruption          7785   \n",
       "45    C0917801                         insomnia          8845   \n",
       "46    C0037763                     muscle spasm          8537   \n",
       "47    C0038454                         apoplexy          7332   \n",
       "48    C0027947                      Neutropenia          6996   \n",
       "49    C0020625           blood sodium decreased          7267   \n",
       "\n",
       "    Mean Permuted Overlap  Probability True < Permuted  \n",
       "0              13817.6665                       1.0000  \n",
       "1              13141.3570                       1.0000  \n",
       "2              12715.3290                       0.0215  \n",
       "3              11998.8955                       1.0000  \n",
       "4              11921.7745                       0.0000  \n",
       "5              11760.4490                       0.0000  \n",
       "6              11740.9805                       0.0000  \n",
       "7              11587.6845                       0.0000  \n",
       "8              11377.2805                       0.0000  \n",
       "9              10890.9000                       0.0000  \n",
       "10             10811.9245                       0.1760  \n",
       "11             10799.2440                       0.0000  \n",
       "12             10627.1125                       0.0000  \n",
       "13             10590.1065                       0.0000  \n",
       "14             10448.3195                       0.0000  \n",
       "15             10073.0220                       0.0000  \n",
       "16              9944.3010                       0.0000  \n",
       "17              9883.8600                       0.0000  \n",
       "18              9689.2270                       1.0000  \n",
       "19              9681.1065                       0.0005  \n",
       "20              9557.3490                       0.0000  \n",
       "21              9503.0730                       0.0000  \n",
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       "32              8874.1120                       0.0000  \n",
       "33              8871.6220                       0.0000  \n",
       "34              8837.0945                       0.9020  \n",
       "35              8620.5610                       0.0000  \n",
       "36              8596.8345                       1.0000  \n",
       "37              8516.5250                       1.0000  \n",
       "38              8367.0850                       1.0000  \n",
       "39              8354.2405                       1.0000  \n",
       "40              8267.0380                       1.0000  \n",
       "41              8072.5870                       1.0000  \n",
       "42              7886.3295                       1.0000  \n",
       "43              7871.2930                       0.0160  \n",
       "44              7860.9235                       0.9425  \n",
       "45              7825.6305                       0.0000  \n",
       "46              7769.9140                       0.0000  \n",
       "47              7722.1020                       1.0000  \n",
       "48              7691.7345                       1.0000  \n",
       "49              7447.0185                       1.0000  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# For nausea\n",
    "run_permutation_test('C0027497')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# How similar are the drug target profiles of drug combinations?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Third, we probe the relationship between proteins targeted by a drug pair and occurrence of side effects. Let $T_i$ represent a set of target proteins associated with drug $i$, we then calculate the Jaccard similarity between target proteins of a given drug pair $(i,j)$ as: $\\text{Jaccard}(i,j) = |T_i \\cap T_j|/|T_i \\cup T_j|$.  \n",
    "We see most drug combinations have zero target proteins in common, random drug pairs have smaller overlap in targeted proteins than co-prescribed drugs, andthat this trend is unequally observed across different side effects. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def jaccard(set1, set2):\n",
    "    num = len(set(set1).intersection(set(set2)))\n",
    "    den = len(set(set1).union(set(set2)))\n",
    "    return num*1.0/den\n",
    "\n",
    "# Only examining those drugs we have drug target information for\n",
    "valid = []\n",
    "for stitch in stitch2se:\n",
    "    if len(stitch2proteins[stitch]) > 0:\n",
    "        valid += [stitch]\n",
    "        \n",
    "# Jaccard similarity between drug target profiles of drugs in drug combinations\n",
    "jaccard_combos = {}\n",
    "for combo in combo2se:\n",
    "    stitch1, stitch2 = combo2stitch[combo]\n",
    "    if stitch1 in valid and stitch2 in valid:\n",
    "        jaccard_combos[combo] = jaccard(stitch2proteins[stitch1], stitch2proteins[stitch2])\n",
    "        \n",
    "# Jaccard similarity between drug target profiles of random drugs\n",
    "jaccard_random = []\n",
    "for i in range(len(jaccard_random)):\n",
    "    stitch1 = np.random.choice(valid, 1, replace=False)[0]\n",
    "    stitch2 =  np.random.choice(valid, 1, replace=False)[0]\n",
    "    jaccard_random += [jaccard(stitch2proteins[stitch1], stitch2proteins[stitch2])] \n",
    "jaccard_random = np.asarray(jaccard_random)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "def plot_jaccard_distribution_multiple(ses):\n",
    "    group_names = {'Random drug pairs': jaccard_random, 'All drug combinations': np.asarray([jaccard_combos[combo] for combo in jaccard_combos])}\n",
    "    order = ['Random drug pairs', 'All drug combinations'] + [nicknames[se] for se in ses]\n",
    "    for se in ses:\n",
    "        se_combos = se2combo[se].intersection(set(jaccard_combos.keys()))\n",
    "        in_jaccard = np.asarray([jaccard_combos[combo] for combo in se_combos])\n",
    "        group_name = nicknames[se]\n",
    "        group_names[group_name] = in_jaccard\n",
    "    categories = {'No shared drug targets': (-.01, 0), 'Fewer than 50% shared': (0, 0.5), 'More than 50% shared':(0.5, 1)}\n",
    "    groups, similarities, fractions = [], [], []\n",
    "    for name in group_names:\n",
    "        arr = group_names[name]\n",
    "        for category in categories: \n",
    "            min_val, max_val = categories[category]\n",
    "            value = np.sum((arr > min_val) * (arr <= max_val))*1.0/len(arr)\n",
    "            groups += [name]\n",
    "            similarities += [category]\n",
    "            fractions += [value]\n",
    "    data = pd.DataFrame({ '' : groups, 'Jaccard Similarity Between Drug Target Profiles': similarities, 'Fraction of Drug Combinations': fractions})\n",
    "    plt.figure(figsize=(3, 5))\n",
    "    sns.set_context(\"paper\", font_scale=6)\n",
    "    sns.set_style('ticks')\n",
    "    sns.set_style({\"xtick.direction\": \"in\", \"ytick.direction\": \"in\"})\n",
    "    g = sns.factorplot(x=\"Jaccard Similarity Between Drug Target Profiles\", y=\"Fraction of Drug Combinations\", hue=\"\", data=data,\n",
    "                   size=18, kind=\"bar\", palette=['#535456', '#9ea3a8', '#3478e5', '#e74c3c', '#2ecc71', '#cc6c18', '#9b59b6',], x_order=['No shared drug targets','Fewer than 50% shared','More than 50% shared'], hue_order=order)\n",
    "    plt.tight_layout()\n",
    "    plt.xlabel('')\n",
    "    plt.savefig('multiple_dist.pdf')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/monicaagrawal/anaconda/lib/python2.7/site-packages/ipykernel/__main__.py:17: RuntimeWarning: invalid value encountered in double_scalars\n",
      "/Users/monicaagrawal/anaconda/lib/python2.7/site-packages/seaborn/categorical.py:3304: UserWarning: The `x_order` parameter has been renamed `order`\n",
      "  UserWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a33346e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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/Tu3VsW08OHD9Vum5iYiBs3bsjmsZ4yZYrGsTVr1kzlfVSMEFDeQkJCpPe4ZCMHV1dXjcqPGzcO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4nea9LYvtCwgIwKpVq2RBjPLly2PYsGHo1asXHBwcYGlpiezs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\ndgx79+5FSEgIlEql1vVq1KiB/v3747PPPoOVlVWh6nr16hX27NmDw4cP4/n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n36tGVH0759e7355psuw/WU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\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4mrDt0NraGj/99JOoCV4jIyP89NNPGDRokFy7V9bm9fT0MGnSJKxYsUIbp4uysjJu5SHD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\nCIIgCIIgCIIgCIIgCIIgCIIgCOKt4P8ADcvxN6fo638AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a0d45b8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nicknames = {'C0035522': 'Rib fracture', 'C0001339': 'Acute pancreatitis', 'C0010200': 'Cough', 'C0021390': 'Inflammatory bowel disease', 'C0020538': 'High blood pressure'}\n",
    "\n",
    "plot_jaccard_distribution_multiple(['C0035522', 'C0001339',  'C0010200', 'C0021390', 'C0020538'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
